Camera normalization

ABSTRACT

Methods, systems, and computer-readable media are provided for camera normalization. Images may be normalized after they are captured to conform to previously captured images. Images may also be preemptively adjusted (prior to capture) to conform to previously captured images.

BACKGROUND

Using images in healthcare has been commonplace for years. Oftenhealthcare imaging focuses on taking patient/person pictures orvisualizing internal organs, but there are just as many cases wheretaking photos from the outside of the body are necessary. These types ofphotos focus on cases of documenting skin conditions including pressureulcers which may be visible from outside the body. In pressure ulcercare, images are taken and reviewed over time to see how a wound ishealing or worsening and guide treatment. The challenge in many of thesecases is that a regular camera is used for capturing the images. Astablets and other mobile devices are integrating cameras and becomingmore common in devices to capture these photos, the differences betweenthe optics and electronics in these devices must be considered. An imagecaptured on a mobile phone, for instance, may look different (in color,contrast, brightness, etc.) from an image captured on a differentdevice. It can be risky to assess and compare the coloration of a woundacross images when the image capturing device is not constant withrespect to how it records/captures that color. Healthcare organizationsmay be at risk for failure to detect conditions using these photos.

SUMMARY

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used as an aid in determining the scope of the claimed subjectmatter.

In brief and at a high level, this disclosure describes, among otherthings, methods, systems, and computer storage media for cameranormalization. Visible light images (i.e., those that are visible to thenaked eye) are commonplace in healthcare. Typical uses may be forwounds, rashes, skin markings (e.g., moles), and the like. Visible lightimages are oftentimes images that are used over a period of time and, assuch, are compared to one another to monitor a subject. As previouslymentioned, multiple image capture devices (e.g., cameras) may beutilized throughout a course of treatment for a patient. Different imagecapture devices may have different properties associated therewith(e.g., zoom settings, lenses, etc.). Additionally, environmental factors(e.g., lighting) may differ between each image of a series of images.These differences should be addressed either after or before subsequentimages are captured.

In a post-capture situation (i.e., the subsequent image has already beencaptured), normalization may be performed on the subsequent image sothat it conforms to previous images. In a pre-capture situation (i.e.,the subsequent image has not yet been captured), a user may be notifiedof one or more adjustments that may be made to make the subsequent imageconform to previous images.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments are described in detail below with reference to the attacheddrawing figures, wherein:

FIG. 1 is a block diagram of an exemplary computing environment suitableto implement embodiments of the present invention;

FIG. 2 is a block diagram of an exemplary system for cameranormalization suitable to implement embodiments of the presentinvention;

FIG. 3 is an exemplary image interface in accordance with an embodimentof the present invention;

FIG. 4 is an exemplary adjustment interface in accordance with anembodiment of the present invention;

FIG. 5 is a flow diagram of an exemplary method of normalizing images inaccordance with an embodiment of the present invention; and

FIG. 6 is a flow diagram of an exemplary method of normalizing images inaccordance with an embodiment of the present invention.

DETAILED DESCRIPTION

The subject matter of the present invention is described withspecificity herein to meet statutory requirements. However, thedescription itself is not intended to limit the scope of this patent.Rather, the inventors have contemplated that the claimed subject mattermight also be embodied in other ways, to include different steps orcombinations of steps similar to the ones described in this document, inconjunction with other present or future technologies. Moreover,although the terms “step” and/or “block” may be used herein to connotedifferent elements of methods employed, the terms should not beinterpreted as implying any particular order among or between varioussteps herein disclosed unless and except when the order of individualsteps is explicitly described.

In brief and at a high level, this disclosure describes, among otherthings, methods, systems, and computer storage media for cameranormalization. Visible light images (i.e., those that are visible to thenaked eye) are commonplace in healthcare. Typical uses may be forwounds, rashes, skin markings (e.g., moles), and the like. Visible lightimages are oftentimes images that are used over a period of time and, assuch, are compared to one another to monitor a subject. As previouslymentioned, multiple image capture devices (e.g., cameras) may beutilized throughout a course of treatment for a patient. Different imagecapture devices may have different properties associated therewith(e.g., zoom settings, lenses, etc.). Additionally, environmental factors(e.g., lighting) may differ between each image of a series of images.These differences should be addressed either after or before subsequentimages are captured. The images described herein may refer to “still”images or images captured from a video. Alternatively, the presentinvention may be applied to videos as well.

The claimed solution is necessarily rooted in computerized healthcaretechnology in order to overcome a problem specifically arising in therealm of computer healthcare information networks, and the claimsaddress the problem of conforming a series of digital images to previousimages. If adhering to the routine, conventional function of providing aseries of images, the images may be non-conforming and differ in waysthat alter display of the image. Conformance of images is critical indiagnosis or treatment of image subjects. The claimed inventionovercomes the limitations of current computer healthcare technology andprovides other benefits that will become clear to those skilled in theart from the foregoing description.

An exemplary computing environment suitable for use in implementingembodiments of the present invention is described below. FIG. 1 is anexemplary computing environment (e.g., medical-informationcomputing-system environment) with which embodiments of the presentinvention may be implemented. The computing environment is illustratedand designated generally as reference numeral 100. The computingenvironment 100 is merely an example of one suitable computingenvironment and is not intended to suggest any limitation as to thescope of use or functionality of the invention. Neither should thecomputing environment 100 be interpreted as having any dependency orrequirement relating to any single component or combination ofcomponents illustrated therein.

The present invention is a special computing system that can leveragewell-known computing system environments or configurations. Examples ofwell-known computing systems, environments, and/or configurations thatmight be suitable for use with the present invention include personalcomputers, server computers, hand-held or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputers, mainframe computers,distributed computing environments that include any of theabove-mentioned systems or devices, and the like.

The present invention might be described in the general context ofcomputer-executable instructions, such as program modules, beingexecuted by a computer. Exemplary program modules comprise routines,programs, objects, components, and data structures that performparticular tasks or implement particular abstract data types. Thepresent invention might be practiced in distributed computingenvironments where tasks are performed by remote processing devices thatare linked through a communications network. In a distributed computingenvironment, program modules might be located in association with localand/or remote computer storage media (e.g., memory storage devices).

With continued reference to FIG. 1, the computing environment 100comprises a computing device in the form of a control server 102.Exemplary components of the control server 102 comprise a processingunit, internal system memory, and a suitable system bus for couplingvarious system components, including data store 104, with the controlserver 102. The system bus might be any of several types of busstructures, including a memory bus or memory controller, a peripheralbus, and a local bus, using any of a variety of bus architectures.Exemplary architectures comprise Industry Standard Architecture (ISA)bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus,Video Electronic Standards Association (VESA) local bus, and PeripheralComponent Interconnect (PCI) bus, also known as Mezzanine bus.

The control server 102 typically includes therein, or has access to, avariety of non-transitory computer-readable media. Computer-readablemedia can be any available media that might be accessed by controlserver 102, and includes volatile and nonvolatile media, as well as,removable and nonremovable media. By way of example, and not limitation,computer-readable media may comprise computer storage media andcommunication media. Computer storage media includes both volatile andnonvolatile, removable and non-removable media implemented in any methodor technology for storage of information such as computer-readableinstructions, data structures, program modules or other data. Computerstorage media includes, but is not limited to, RAM, ROM, EEPROM, flashmemory or other memory technology, CD-ROM, digital versatile disks (DVD)or other optical disk storage, magnetic cassettes, magnetic tape,magnetic disk storage or other magnetic storage devices, or any othermedium which can be used to store the desired information and which canbe accessed by control server 102. Communication media typicallyembodies computer-readable instructions, data structures, programmodules or other data in a modulated data signal such as a carrier waveor other transport mechanism and includes any information deliverymedia. The term “modulated data signal” means a signal that has one ormore of its characteristics set or changed in such a manner as to encodeinformation in the signal. By way of example, and not limitation,communication media includes wired media such as a wired network ordirect-wired connection, and wireless media such as acoustic, RF,infrared and other wireless media. Combinations of any of the aboveshould also be included within the scope of computer-readable media.

The control server 102 might operate in a computer network 106 usinglogical connections to one or more remote computers 108. Remotecomputers 108 might be located at a variety of locations in a medical orresearch environment, including clinical laboratories (e.g., moleculardiagnostic laboratories), hospitals and other inpatient settings,veterinary environments, ambulatory settings, medical billing andfinancial offices, hospital administration settings, home healthcareenvironments, and clinicians' offices. Clinicians may comprise atreating physician or physicians; specialists such as surgeons,radiologists, cardiologists, and oncologists; emergency medicaltechnicians; physicians' assistants; nurse practitioners; nurses;nurses' aides; pharmacists; dieticians; microbiologists; laboratoryexperts; laboratory technologists; genetic counselors; researchers;veterinarians; students; and the like. The remote computers 108 mightalso be physically located in nontraditional medical care environmentsso that the entire healthcare community might be capable of integrationon the network. The remote computers 108 might be personal computers,servers, routers, network PCs, peer devices, other common network nodes,or the like and might comprise some or all of the elements describedabove in relation to the control server 102. The devices can be personaldigital assistants or other like devices.

Computer networks 106 comprise local area networks (LANs) and/or widearea networks (WANs). Such networking environments are commonplace inoffices, enterprise-wide computer networks, intranets, and the Internet.When utilized in a WAN networking environment, the control server 102might comprise a modem or other means for establishing communicationsover the WAN, such as the Internet. In a networking environment, programmodules or portions thereof might be stored in association with thecontrol server 102, the data store 104, or any of the remote computers108. For example, various application programs may reside on the memoryassociated with any one or more of the remote computers 108. It will beappreciated by those of ordinary skill in the art that the networkconnections shown are exemplary and other means of establishing acommunications link between the computers (e.g., control server 102 andremote computers 108) might be utilized.

In operation, an organization might enter commands and information intothe control server 102 or convey the commands and information to thecontrol server 102 via one or more of the remote computers 108 throughinput devices, such as a keyboard, a microphone (e.g., voice inputs), atouch screen, a pointing device (commonly referred to as a mouse), atrackball, or a touch pad. Other input devices comprise satellitedishes, scanners, or the like. Commands and information might also besent directly from a remote healthcare device to the control server 102.In addition to a monitor, the control server 102 and/or remote computers108 might comprise other peripheral output devices, such as speakers anda printer.

Although many other internal components of the control server 102 andthe remote computers 108 are not shown, such components and theirinterconnection are well known. Accordingly, additional detailsconcerning the internal construction of the control server 102 and theremote computers 108 are not further disclosed herein.

Turning now to FIG. 2, a block diagram 200 is illustrated, in accordancewith an embodiment of the present invention, showing an exemplary systemfor camera normalization. It will be understood and appreciated that thecomputing system shown in FIG. 2 is merely an example of one suitablecomputing system environment and is not intended to suggest anylimitation as to the scope of the user or functionality of embodimentsof the present invention. Neither should the computing system beinterpreted as having any dependency or requirement related to anysingle component or combination of components illustrated therein.Further, although the various block of FIG. 2 are shown with lines forthe sake of clarity, in reality, delineating various components is notso clear, and metaphorically, the lines would more accurately be greyand fuzzy. In addition, any number of physical machines (such ascomputing devices or portions of computing devices shown in FIG. 1),virtual machines, data centers, endpoints, or combinations thereof maybe employed to achieve the desired functionality within the scope ofembodiments of the present invention.

The components of FIG. 2 are capable of communicating with a number ofdifferent entities or data sources such as database 202 for thecollection of data. This communication may utilize, without limitation,one or more local area networks (LANs) and/or wide area networks (WANs).Such networking environments are commonplace in offices, enterprise-widecomputer networks, intranets, and the Internet. Accordingly, the network201 is not further described herein. As used throughout thisapplication, the term “healthcare data” is meant to be broad andencompass any type of healthcare information. The healthcare data may bespecific to a single patient or a group of patients. The healthcare datamay also be directed to a clinician or group of clinicians. For example,healthcare data as it relates to a clinician may include patients thatthe clinician treats.

Returning now to FIG. 2, the exemplary system 200 includes a database202, a user device 203, and a normalization engine 204. The database 202may be any data store capable of storing data relevant to images. Thedatabase 202 may include a conversion table of known image capturedevices with all properties associated therewith. The conversion tablemay include adjustments for images captured by various devices toconform to images captured by other devices.

The user device 203 represents any user devices used to capture ordisplay images. Exemplary user devices include cameras, workstations,laptops, tablets, mobile phones, etc. The user device 203 may be anydevice that includes a camera.

The normalization engine 204 may be any device configured for cameranormalization. The camera normalization includes normalizing imagespost-capture, normalizing images pre-capture, normalization of cameras,and the like. The normalization engine comprises an identifyingcomponent 205, a normalizing component 206, and a notification component207.

The identifying component 205 may be configured for, among other things,identifying properties of images and differences between properties ofsequential images. The identifying component 205 may identifydifferences in sequential images after the images are captured. Theidentifying component 205 may identify differences in sequential imagesprior to capturing the sequential image. This may occur when an imagecapture device is ready to capture a sequential image (e.g., anindication that a sequential image is about to be captured is received)but the image has not yet been captured. An indication that a sequentialimage is about to be captured may be an input into a patient'selectronic health record (EHR) that a sequential image is to be capturedand input in the EHR or the like.

The properties may be identified by the identifying component 205 fromwithin metadata associated with each image (in the post-captureembodiment). Each image may be associated with metadata including adevice identifier of the image capture device that captured the image, atime stamp of the image, and the like. In embodiments, specificproperties of the device are included in the metadata. In otherembodiments, properties of the device are automatically looked up (e.g.,by the computing system) in a device conversion table or on-line basedon a type of device capturing the image. Additional data that may beincluded with each image is related to a patient position during theimage capture (e.g., patient was sitting/standing/lying down, etc.). Insome embodiments, patient physiological data may also be automaticallyassociated with an image such as temperature, blood pressure, pulse,edema, etc. For example, the system may receive patient physiologicaldata (e.g., from patient monitoring equipment, from input in a patient'selectronic health record, etc.) and automatically link the physiologicaldata with relevant images.

Images may also be automatically tagged with details on location andweather conditions for which the image was captured. The system may beconfigured to automatically receive or retrieve information such asweather and a location (e.g., from a GPS) and tag an image with theinformation. For example, on a sunny day (as evidenced by data gatheredautomatically by the system from a weather report and a GPS location ofa camera when the image was taken) a note may be made and tagged on theimage to be aware that the image may be washed out. Similarly, a stormyor cloudy day will also affect brightness of an image. This may not berelevant in all cases (e.g., environment where there are no windows).

Environmental details may also be provided such as lighting in a room. Alink from building management systems may be fed to the system 200 tolink this data with data tagged on images. Lighting detail information,for example, may be linked based on the location of the image when theimage was captured and lighting information for that location.Additional links may allow a camera to adjust the lighting through abuilding management system to change the lighting to match expected orstandard lighting conditions or, alternatively, to match lightingconditions of other images previously captured for the patient.

The normalizing component 206 may be configured for, among other things,normalizing images, camera, and the like. As mentioned, thenormalization may take the form of normalizing images after they arecaptured. The normalization may also be preemptive in the form ofidentifying preemptive measures to take prior to capturing an image tomake sure it conforms to previously captured images.

The notification component 207 may be configured for, among otherthings, providing notifications indicating a series of images do notconform to each other, one or more adjustments to be made to make imagesconform to one another, and the like. The notifications may be promptedprior to an image capture, during a comparison of images, and the like.The notifications may include adjustments to make to ensure the imagesconform to one another. Alternatively, the notification may onlyindicate that two photos do not conform to one another and should not beused for clinical comparisons.

In application, one or more image capture devices are used for capturingvisible light images (i.e., visible to the naked eye in contrast toX-rays, MRI's, and the like). A single facility (e.g., a hospital) mayhave several different image capture devices within the facility.Differences between those devices, and the images captured thereon,should be addressed. For instance, exemplary properties that may differamong sequential images (captured on different or the same devices)include lighting, sizing, zoom, etc. The normalization discussed hereinapplies to both post-capture and pre-capture scenarios where the systemautomatically identifies non-conforming properties without human inputor intervention. Thus, the system automatically compares properties ofimages when selected to compare (post-capture) and automaticallycompares properties of existing images with an image to be captured(pre-capture) to ensure as many images conform to one another forcomparison as possible.

FIG. 3 provides an exemplary interface 300 for a post-capture scenario.As provided in FIG. 3, a plurality of images (image 310, image 320,image 330, and image 340) is provided. The images may be a thumbnailview. As shown, each image may be associated with data that may bedisplayed within the interface 300. Image 310 is associated, forinstance, with a time stamp 311, a device identifier 312, and devicedetails indicator 313. The time stamp 311 indicates a time the image 310was captured (e.g., date and time). The device identifier 312 indicatesan image capture device that captured the image 310. The device detailsindicator 313, upon selection thereof, provides additional detailsrelated to the device indicated by the device identifier 312. Forexample, lens information, among other things, may be provided in thedetailed section. In an alternative embodiment, the details may belisted directly in the interface 300. As is shown in the interface 300,each of the other images is also associated with the same indicators.Image 320 is associated with a time stamp 321, a device identifier 322,and a device details indicator 323. Image 330 is associated with a timestamp 331, a device identifier 332, and a device details indicator 333.Image 340 is associated with a time stamp 341, a device identifier 342,and a device details indicator 343. In embodiments, properties thatdiffer (e.g., device identifiers that are different) may be highlightedto draw a user's attention to differing properties. In additionalembodiments, images captured on the same device are highlighted in thesame color to easily identify images that can be easily compared.

Each image is also associated with a compare indicator (i.e., compareindicators 314, 324, 334, and 344). The compare indicators, whenselected, indicate which images are to be compared to one another. In anembodiment, the differing properties are not highlighted until selectionof at least two compare indicators is identified. This may be becauseuntil a user has decided to compare images, it may not be necessary tohighlight differences between images.

Each image is also associated with a filter out indicator (i.e., filterout indicators 315, 325, 335, and 345). The filter out indicators, whenselected, indicate that any images that are non-conforming to theselected images should be filtered out. Alternatively, the images thatare non-conforming may be highlighted. A continue indicator 350 isprovided for a user to continue with a comparison or a filterinstruction, depending on the selections made in interface 350. Finally,an add new indicator 360 is provided in FIG. 3 for selection when a userwould like to add a new image to the series.

FIG. 4 provides an exemplary interface 400 for a pre-capture scenario.FIG. 4 provides an image subject 410 (in this case a patient's arm/hand)and a notification 420. In this displayed scenario, an image is about tobe taken with an image capture device. The image and notification may bepresented on the image capture device itself or on a separate device(e.g., an image capture device is positioned above the subject areawhile an image is presented on a separate computer for viewing by auser). The notification 420 may include a warning 430 that adjustmentsshould be made to conform to a given image. The indication of a previousimage may be indicated by a user or may be identified by the system 200from the patient's EHR. For example, the system 200 may identifyprevious images for a patient when a new image is to be added. Thenotification 420 may also include one or more adjustments 440 to make toan image to conform to a previous image (the identified previous imagein the warning 430, for instance). The adjustments may include zoomingin, zooming out, adjusting the lighting in the room/environment, and thelike.

In embodiments, thermal imaging sensors are leveraged to detect andoverlay temperature data on an image. This thermal imaging informationis valuable in the treatment of wounds, for example, where blood cellsrush to the area during healing (resulting in warmer temperatures).Thermal sensors may assist in monitoring healing of wounds. Byoverlaying the temperature data over images, comparisons may be easilymade and a stage of healing identified.

Additional embodiments include overlaying depth and other spatialmeasurement data over images during image acquisition to allow the imageacquirer (e.g., the device capturing the photo) to match a previouslycaptured image to said new image currently being captured to allow forbetter future comparison. Overlaying a scale on the viewfinder whilecapturing a new image will allow a new image to be taken atsubstantially the same angle and distance as previous images.Notifications may be provided guiding a user through matching up thescales. For example, a notification indicating a user was 3 inchescloser in the previous image may be provided.

Turning now to FIG. 5, a flow diagram illustrating an exemplary method500 is provided. Initially, at block 510, a selection of a first imageto compare is received. One or more properties of the first image areidentified at block 520. A selection of a second image to compare to thefirst image is received at block 530 and one or more properties of thesecond image are identified at block 540. At least one property of thesecond image that differs from a corresponding property of the firstimage is identified at block 550. At block 560, the second image isautomatically normalized so that the at least one property of the secondimage matches the corresponding property of the first image.

Turning now to FIG. 6, a flow diagram illustrating an exemplary method600 is provided. Initially, at block 610, an indication of a secondimage to be taken for a patient is received. One or more properties ofthe first image are identified at block 620. At block 630, a firstproperty of the one or more properties of the first image that does notmatch a corresponding second property of the second image to be taken isidentified. At block 640, a notification of one or more adjustments tomake prior to capture of the second image to make the second imageconform to the first image is provided.

Many different arrangements of the various components depicted, as wellas components not shown, are possible without departing from the spiritand scope of the present invention. Embodiments of the present inventionhave been described with the intent to be illustrative rather thanrestrictive. Alternative embodiments will become apparent to thoseskilled in the art that do not depart from its scope. A skilled artisanmay develop alternative means of implementing the aforementionedimprovements without departing from the scope of the present invention.

It will be understood that certain features and subcombinations are ofutility and may be employed without reference to other features andsubcombinations and are contemplated within the scope of the claims. Notall steps listed in the various figures need be carried out in thespecific order described. Accordingly, the scope of the invention isintended to be limited only by the following claims.

What is claimed is:
 1. A system for normalization, the systemcomprising: one or more processors of a normalization engine; and one ormore computer storage media storing computer-executable instructionsthat, when executed by the one or more processors of the normalizationengine, implement a method comprising: receiving a selection of a firstimage to compare, wherein the first image was captured in a firstenvironment; identifying a first set of properties of the first image,wherein at least a first property of the first set of properties isassociated with a first camera device, and wherein a second property ofthe first set of properties is associated with the first environment;receiving a selection of a second image to compare to the first imagewherein the second image was captured in a second environment;identifying a second set of properties of the second image, wherein atleast a first property of the second set of properties is associatedwith a second camera device wherein a second property of the second setof properties is associated with the second environment, and wherein thesecond environment is different from the first environment; identifyingat least one property of the second image that differs from acorresponding property of the first image; and automatically normalizingthe second image so that the at least one property of the second imagematches the corresponding property of the first image, wherein thesecond image is normalized using a conversion table comprisingproperties of the first camera device, the second camera device, thefirst environment and the second environment.
 2. The system of claim 1,wherein the first property of the first image includes the first cameradevice that captured the first image and camera settings of the firstcamera device while capturing the first image.
 3. The system of claim 2,wherein the second property of the first image further includes alighting descriptor of the first environment where the first image wascaptured.
 4. The system of claim 1, wherein the first property of thesecond image includes the second camera device that captured the secondimage and camera settings of the second camera device while capturingthe second image.
 5. The system of claim 4, wherein the second propertyof the second image further includes a lighting descriptor of the secondenvironment where the second image was captured.
 6. The system of claim1, wherein the at least one property of the second image that differsfrom the corresponding property of the first image is a lightingproperty.
 7. The system of claim 6, wherein the second image isnormalized by adjusting a brightness of the second image.
 8. Acomputerized method carried out by a normalization engine having atleast one processor for normalizing images, the method comprising:receiving a selection of a first image captured by a first camera devicein a first environment to compare; identifying a first set of propertiesof the first image, wherein a first property of the first set ofproperties is associated with the first camera device, and wherein asecond property of the first set of properties is associated with thefirst environment; receiving a selection of a second image captured by asecond camera device in a second environment to compare to the firstimage; identifying a second set of properties of the second image,wherein a first property of the second set of properties is associatedwith the second camera device, and wherein a second property of thesecond set of properties is associated with the second environment, andwherein the second environment is different from the first environment;identifying at least one property of the second set of properties of thesecond image that differs from a corresponding property of the firstimage; and automatically normalizing the second image so that the atleast one property of the second image matches the correspondingproperty of the first image, wherein the second image is normalizedusing a conversion table comprising properties of the first cameradevice, the second camera device, the first environment, and the secondenvironment.
 9. The computerized method of claim 8, wherein the at leastone property of the second image that differs from the correspondingproperty of the first image is a lighting property.
 10. The computerizedmethod of claim 9, further comprising normalizing the second image byadjusting a brightness of the second image.
 11. The computerized methodof claim 8, wherein the first property of the first image includes thefirst camera device that captured the first image and camera settings ofthe first camera device while capturing the first image.
 12. Thecomputerized method of claim 11, wherein the second property of thefirst image includes a lighting descriptor of the first environmentwhere the first image was captured.
 13. The computerized method of claim11, wherein the first property of the second image includes the secondcamera device that captured the second image, camera settings of thesecond camera device while capturing the second image, and the secondproperty of the second image includes a lighting descriptor of thesecond environment where the second image was captured.